The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Study on the Prediction of Traffic Counts Based on Shortest Travel Path

최단경로 기반 교통량 공간 예측에 관한 연구

  • 허태영 (한국해양대학교 나노데이터시스템학부 데이터정보) ;
  • 박만식 (고려대학교 의과학연구원 유전체및단백체환경독성센터) ;
  • 엄진기 (한국철도기술연구원 철도정책물류연구본부) ;
  • 오주삼 (한국철도기술연구원 첨단도로교통연구실)
  • Published : 2007.11.30
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Abstract

In this paper, we suggest a spatial regression model to predict AADT. Although Euclidian distances between one monitoring site and its neighboring sites were usually used in the many analysis, we consider the shortest travel path between monitoring sites to predict AADT for unmonitoring site using spatial regression model. We used universal Kriging method for prediction and found that the overall predictive capability of the spatial regression model based on shortest travel path is better than that of the model based on multiple regression by cross validation.

본 연구에서는 연평균일교통량 예측을 위한 공간회귀모형을 제시하였다. 비록 공간 분석을 위하여 조사지점들 간의 유클리디안 거리가 일반적으로 사용되고 있지만, 조사되지 않는 도로의 교통량 예측을 위하여 교통량 조사지점들 간의 최단경로를 이용한 공간회귀모형을 새롭게 시도하였다. 공간예측방법으로는 일반크리깅을 사용하였으며 교차검증을 통하여 정량적으로 최단경로 기반의 교통량공간예측모형의 타당성을 제시하였다.

Keywords

References

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